• Source: Scopus
  • Calculated based on no. of publications stored in Pure and citations from Scopus
20172019

Research output per year

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Personal profile

Personal profile

Michael Bewong is a lecturer in computing (Data Science, AI and Cyber Security) at Charles Sturt University. His ambition is to utilize his expertise in the field of data analytics collaboratively to solve real world problems; and to share this knowledge through research publications and teaching.

Prior to joining Charles Sturt, he worked as a course coordinator and a research fellow for University of South Australia (UniSA). As a course coordinator he taught database related subjects. As a research fellow he worked collaboratively with Data to Decisions Cooperative Research Centre (D2D CRC) on various projects. These include the “Beat the News” project where he developed data mining models for predicting socially disruptive events. He also worked on the project “Predicting Cyber Security Exploits”, where he developed novel machine learning techniques to address the challenges in predicting exploits of vulnerabilities within the cyber security space.

Teaching

Michael Bewong’s teaching interests include topics in data science, databases and cyber security. He currently teaches/moderates the following subjects at Charles Sturt University:

  • Network Security and Cryptography (ITC593)
  • Data and Knowledge Engineering (ITC573)
  • Data Mining and Visualisation for Business Intelligence (ITC516)
  • Foundations of Big Data Analytics (ITC575)

Research Interests

Michael Bewong’s research interests are in the areas of privacy preservation, cyber security, data mining, and databases.

His current research focusses on data analytics in social media and its applications to cybersecurity. Particularly he is currently working on (1) improving topic discovery from text data; (2) developing novel techniques for predicting exploits of cyber security vulnerabilities and; (3) opinion summarisation from social media.

His previous research mainly focussed on developing privacy preserving data publication algorithms for both structured and unstructured data.

Please see Michael's publications for his recent works.

He is also an active reviewer for top journals and conferences including TKDE, SDM, KDD, PAKDD, WSDM.

Michael is happy to chat to potential PhD and Honours students about research supervision within his research area.

Professional Information

  • Member, Engineers Australia
  • Member, Association of Computing and Machinery (ACM)
  • Member, Institute of Electrical and Electronics Engineers (IEEE)
  • Sponsorship Chair for AusDM 2019

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